The venerable Western Hemlock - Washington’s state tree - has been in decline in the Puget Lowlands since at least 2015. These trees are dying - not everywhere all at once - as with HWA and the Eastern Hemlock - but intermittently, often in clusters throughout low elevations west of the Cascades. This mortality is recent, and a departure from normal hemlock population dynamics, and the well-understood effects of endemic fungal diseases.

By 2017, researchers were attributing the mortality to Rhizoctonia butini, a fungus in the order Cantharellales. This hypothesis has since been abandoned (according to personal communications form Jared LeBoldus, OSU Corvallis, and Kevin Zobrist, WSU). No new explanation has emerged, but we often hear the suggestion that the mortality is due to normal old age or maybe climate change.

A few years of informal observation in Seward Park’s 120-acre old-growth urban forest, however, leads us to suggest otherwise. We see areas with many dead trees. We have watched large trees die. We also see areas nearby, sharing climate and weather, dense with healthy trees of all ages.

So we suspect other causes are at play. To justify research into those possible other causes, we conducted an in-depth survey, mapping, measuring and assessing the health of 724 Western Hemlocks in Seward Park’s forest. The survey, as you will see, provides strong statistical evidence that neither climate nor normal senesence is responsible the mortality.

Futhermore, our findings suggest that this forest provides an ideal site for a natural experiment, an excellent opportunity for deeper research into the mechanisms of Puget Lowland Western Hemlock decline.

Mapping and Measuring at Seward Park

Between January and March, two Univeristy of Washington students from the Program on the Environment in their senior Capstone Research Project, along with a Garfield High School junior, guided by Dr. Tim Billo of the UW, spent nine weeks in the forest collecting data to test our hypothesis. The study participants are listed in Appendix B, below.

We also used data collected in the summer of 2021 by CHOOSE 180 interns.

We took these steps in the study:

  1. We initially identified a two acre healthy site (the “hemlock garden”) and a six acre affected site (the “hemlock graveyard”). This site has been expanding slowly over the last five years.
  2. We mapped, measured and assessed the health of all trees in these two sites.
  3. We found that the sites, separated within continuous old-growth forest by 700 meters, were identical except for mortality: they have the same size distribution, see the weather patterns, and have the same type of soil.
  4. We next expanded our survey to include 724 total hemlocks across most of the 120-acre forest

Our Results


(An interactive version of the above map, along with the full dataset, is available here.)

After mapping, measuring, and assessing the health of 724 trees across a broad swath of the 120-acre forest, skipping over regions with few or no hemlocks, we partitioned the trees into those with good-to-excellent health (greater than 2 on a 0-3 scale, see Appendix C), and those with poor health (less than 1 on that same scale).

This mapping, and subsequent density calculations, allowed us to confirm the hemlock graveyard, and to define the “extended garden”, which is much larger than our originally identified healthy site. We see sick and dying trees are heavily concentrated in a contiguous region in the north of the forest. Healthy hemlocks are found south, central and east in the forest.

We establish that the hemlock graveyard is a highly significant outlier with respect to hemlock mortality in this forest. And we lay to rest claims that the mortality is due only to climate change or normal senescence.

The Climate Change Claim

This is easily dispensed with. Or, at least, reduced to a minor role. The two regions may have significant micro-climate differences, or micro-site characteristics which contribute to differential mortality. But it is unlikely that decade-scale climate change phenomena, showing up as significant differences in micro-scale weather patterns, will explain the radical mortality difference of the two regions, graveyard and garden.

The Natural Senescence Claim

Here we show that big old trees are roughly equally represented in the two regions, but that the health of those trees is dramatically different. (See Appendix A, below, explainiing omission of younger trees.)

Significance Tests

The Student’s t-Test complements these boxplots, producing a numerical value for the contrasts you see visually above.

With respect to tree size (which roughly correlates with tree age) the two sites have the same distribution. A p.value of larger that 0.7 attests that these groups are highly similar.

dbh.threshold <- 15
garden.bigTrees.dbh <- subset(tbl, loc=="garden" & dbh > dbh.threshold)$dbh
graveyard.bigTrees.dbh <- subset(tbl, loc=="graveyard" & dbh > dbh.threshold)$dbh

t.test(graveyard.bigTrees.dbh, garden.bigTrees.dbh)$p.value
## [1] 0.71514

This p.value, less than l0e-15, indicates that the contrast in hemlock health across the two regions is highly significant. This is our our major finding.

garden.bigTrees.health <- subset(tbl, loc=="garden" & dbh > dbh.threshold)$h
graveyard.bigTrees.health <- subset(tbl, loc=="graveyard" & dbh > dbh.threshold)$h

t.test(graveyard.bigTrees.health, garden.bigTrees.health)$p.value
## [1] 6.168258e-16




Conclusion


Our nine-week citizen and student science study establishes that
  1. Seward Park’s old-growth forest hemlock die-off is dramatic and concentrated in one (expanding) six acre region.
  2. is not caused simply by senescence or weather patterns,
  3. that it provides an opportunity for further (professional) study.
We predict that foliar and mycorrhizal DNA sequencing, entomological studies, and root rot analyses may all be needed to understand this problem. Once understood, remedies may be found, further decline and symptom spread may be prevented.


We offer one caveat in closing. Our past visits to other affected sites suggested that Seward mortality, and regional mortality, look like the same phenomenon. But in this study we did not collect observations at other locations. Therefore we have not established that Seward’s hemlock mortality, and that of the region, are identical. Detailed field observations may decide this. Laboratory and molecular methods may be needed.




Appendix A: Filtering Trees by Size Before Comparing Health

When addressing the claim that hemlocks at Seward are dying because of old age - that is, due to normal Puget Lowland hemlock senescence - we above filtered out all trees less than 10 inches diameter at breast height, dhb.

We motivate and justify this filtering here.

First, let us examime the relative ages of graveyard trees and garden trees.

hist(subset(tbl, loc=="garden")$dbh, main="Garden DBH", xlab="inches", xlim=c(0,60), ylim=c(0,120))

hist(subset(tbl, loc=="graveyard")$dbh, main="Graveyard DBH", xlab="inches", xlim=c(0,60), ylim=c(0,120))

We see that there is an abundance of small diameter hemlocks in the garden, and comparitively few in the graveyard. If we compare all sizes (all ages) in both groups, we will see that, and be misled by, their being approximately equal distribution in the graveyard across all sizes.

(Two explanations for the paucity of young trees in the graveyard occur to us; there may be others. First, that this region is no longer conducive to hemlock growth for trees of any age, including seedlings and saplings. Second, the heavy mortality of larger trees may have lead to diminished seed source in recent years.)

boxplot(subset(tbl, loc=="graveyard")$dbh,
           subset(tbl, loc=="garden")$dbh,
        main="DBH (a proxy for age; all trees included)",
        names=c("Graveyard", "Garden"))

In this view, the distribution of trees in the graveyard - all trees - is somewhat larger.

However, this boxplot does not answer the question we are actually asking in this study: are hemlocks dying due to old age? We can best answer this by comparing the health of large trees in the two populations: apples to apples, big (old) trees to big (old) trees.

We can see that the distribution of older trees is roughly similar in the two groups:

boxplot(subset(tbl, loc=="graveyard" & dbh >= 15)$dbh,
        subset(tbl, loc=="garden" & dbh >= 15)$dbh,
        main="DBH (a proxy for age; larger trees only)",
        names=c("Graveyard", "Garden"))

With a cutoff of 15 inches dbh, we have comparable populations.

Now let’s compare their health.

boxplot(subset(tbl, loc=="graveyard" & dbh >= 15)$h,
        subset(tbl, loc=="garden" & dbh >= 15)$h,
        main="Health - larger trees only",
        names=c("Graveyard", "Garden"))

And obtain their t.test pvalue, which estimates the likelihood that the population difference could occur by chance.

t.test(subset(tbl, loc=="graveyard" & dbh >= 15)$h,
       subset(tbl, loc=="garden" & dbh >= 15)$h)$p.value
## [1] 2.103177e-16



Appendix B: Participants





Appendix C: Hemlock Health Assessment


We adapted aspects of the DMR (Dwarf Mistletoe Rating) system, originally suggested to us by Marianne Elliott in 2021. Our proxy for health was an informal estimate of the robustness and extent of needles on each third of the tree.

In our scheme, h1 is the bottom third of the tree, h2 is the middle third, and h3 the top. Each section received a number on a scale of 0 (no remaining needles) to 3 (abundant needles, no significant bare branches).

We learned early in the project that mature hemlocks, especially those which are in the canopy exposed to direct sun, self-prune their lower branches. In these cases we assigned the value NA to the lower thirds of the tree, so that the tree’s evolved response to canopy status is not counted as ill-health.

For each tree, we calculate a composite score, the average of the three section scores.

These ratings, and indeed the informal division of each tree’s trunk into thirds, are imprecise. Nonetheless, after the first few days in the field, all four of us easily reached consensus on each tree that we encountered, suggesting that these informal ratings can be easily reproduced by independent observers.

Understory trees usually fit the original model, in which bare, needle-sparese or recently fallen lower branches are a sign of ill-health.

Perhaps the best description of our method is that we assign grades of ill-health based on the evidence of failing needles, branchlets and branches where, according to healthy Western Hemlock needle and branch patterns, we expect them to flourish. In essence, our method was a consensus arising from negotiation of four ‘human phenocams’.

The DMR (Dwarf Mistletoe Rating) is described here.

Appendix D: Kernel Density Calculations


(To be expanded, will include working code and contour maps).

The method, all carried out in R 4.3.1

Using kde2d from the MASS package:

tbl.h <- subset(tbl, h>=2) # | h <= 1)
f.healthy <- kde2d(tbl.h$lon, tbl.h$lat, n=cellCount, lims=seward.limits)
z <- f.healthy$z
range(z)
z[z <min.density] <- 0
f.healthy$z <- z
range(f.healthy$z)
image(f.healthy, main="healthy", col=healthy.colors) #, zlim = c(0, 0.05))
#dev.off()
contour(f.healthy, xlab = "healthy", add=TRUE)
contours.healthy <- contourLines(f.healthy)
length(contours.healthy)  # 9

Using pointsInPolygon from the secr package:

fb1 <- "gardenBoundaries.json"
fb2 <- "graveyardBoundaries.json"
tbl.garden <- fromJSON(fb1)
dim(tbl.garden)  # 949 2
tbl.graveyard <- fromJSON(fb2)
dim(tbl.graveyard) # 395 2

colnames(tbl.garden) <- c("y", "x")
tbl.garden <- tbl.garden[, c("x", "y")]

colnames(tbl.graveyard) <- c("y", "x")
tbl.graveyard <- tbl.graveyard[, c("x", "y")]


in.garden <- which(pointsInPolygon(tbl[, c("lon", "lat")], tbl.garden))  # 448
in.graveyard <- which(pointsInPolygon(tbl[, c("lon", "lat")], tbl.graveyard))  # 144
length(intersect(in.garden, in.graveyard))  # 0
location <- rep("none", nrow(tbl))
location[in.garden] <- "garden"
location[in.graveyard] <- "graveyard"
table(location)
tbl$loc <- location

Appendix E: Estimating the Age of Healthy Hemlocks in the Garden

In a 1983 journal article, Mark Harmon and Jerry Franklin offer a linear model relating Western Hemlock age in years to diameter in centimeters:

Age Distribution of Western Hemlock and Its Relation to Roosevelt Elk Populations in the South Fork Hoh River Valley, Washington

Their model comes from direct measurment, of diameter at breast height, and of tree age by counting rings after increment boring. If we apply their formula, while acknowledging that the Hoh River Valley receives four times as much rain as Seward Park, we find this profile of tree age.

dbh <- subset(tbl, loc=="garden" & h > 2.5)$dbh
dbh.cm <- 2.54 * dbh
age <- round(30.5 + (1.8 * dbh.cm))
hist(age, main="Estimaged Age\n for 185 Healthy Hemlock Garden trees", xlab="years",
     xlim=c(0,300))

The fire history of Seward’s forest may be relevant here. We believe that a stand replacement fire swept the peninsula about 1500. A more moderate fire burned through about 1720, survived by about 100 firs and a dozen cedars. Our oldest hemlocks may have seeded in within fify years of the more recent fire, as the surving douglas firs, and younger trees (maples? cedars?) formed a new canopy. [This fire history is drawn from diverse sources and is somewhat conjectural.]